Digital images of an object or scene that have been captured, for example, via a digital camera or a scanner, generally include an amount of noise that is encoded within the digital image. Noise, such as Gaussian noise, within a digital image can generally be described as a random plus or minus deviation at each pixel location of the digital image. This random plus or minus deviation is often introduced into the digital image via the sensor that is utilized to capture the digital image and can be affected by poor illumination of the object or scene, temperature of the sensor at the moment when the object or scene is captured, electronic noise within the circuit that is utilized to capture the digital image, etc. A common source of noise in a reasonably exposed image is shot noise, which is an unavoidable phenomenon due to the nature of converting incoming light into an electrical charge on the image sensor. While noise is generally considered undesirable, the human eye has come to expect noise within a captured digital image and can readily discern when the noise across an image varies or strays from an amount of noise expected.
When a digital image is blurred, for example utilizing a graphics editor to apply a blur to the digital image, the amount of noise within the digital image is reduced in correlation with how much the digital image is blurred. Current blur techniques can result in a spatially varying blur across a digital image such that the amount of blur varies from one portion of the digital image to another. As a result, the noise that occurs across the digital image would also vary, which, as mentioned previously, is readily discernable to the human eye and generally detracts from the aesthetics of the object or scene depicted by the digital image.
While there are various techniques that have been developed for adding noise back into a digital image that has been blurred, none of these techniques accurately account for the amount of noise lost during the blur process, nor do they accurately account for how noise behaves when adding noise back into the digital image.